Pandas Profiling Report

Dataset statistics

Number of variables	14
Number of observations	1512
Missing cells	272
Missing cells (%)	1.3%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	160.3 KiB
Average record size in memory	108.5 B

Variable types

Numeric	8
Categorical	6

Alerts

`original_plataform` has constant value "Netflix"	Constant
`titles` has a high cardinality: 1512 distinct values	High cardinality
`genres` has a high cardinality: 247 distinct values	High cardinality
`description` has a high cardinality: 1471 distinct values	High cardinality
`stars` has a high cardinality: 1461 distinct values	High cardinality
`level_0` is highly correlated with `df_index`	High correlation
`df_index` is highly correlated with `level_0`	High correlation
`number_of_votes` is highly correlated with `nueva_columna`	High correlation
`nueva_columna` is highly correlated with `number_of_votes`	High correlation
`level_0` is highly correlated with `df_index`	High correlation
`df_index` is highly correlated with `level_0`	High correlation
`level_0` is highly correlated with `df_index`	High correlation
`df_index` is highly correlated with `level_0`	High correlation
`number_of_votes` is highly correlated with `nueva_columna`	High correlation
`nueva_columna` is highly correlated with `number_of_votes`	High correlation
`original_plataform` is highly correlated with `type`	High correlation
`type` is highly correlated with `original_plataform`	High correlation
`runtime` has 240 (15.9%) missing values	Missing
`stars` has 28 (1.9%) missing values	Missing
`level_0` is uniformly distributed	Uniform
`df_index` is uniformly distributed	Uniform
`titles` is uniformly distributed	Uniform
`stars` is uniformly distributed	Uniform
`level_0` has unique values	Unique
`df_index` has unique values	Unique
`titles` has unique values	Unique

Reproduction

Analysis started	2022-03-05 12:26:33.509770
Analysis finished	2022-03-05 12:26:43.178188
Duration	9.67 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

level_0
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct	1512
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	757.9444444

Minimum	0
Maximum	1516
Zeros	1
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	11.9 KiB

Quantile statistics

Minimum	0
5-th percentile	76.55
Q1	379.75
median	757.5
Q3	1136.25
95-th percentile	1440.45
Maximum	1516
Range	1516
Interquartile range (IQR)	756.5

Descriptive statistics

Standard deviation	437.799282
Coefficient of variation (CV)	0.5776139468
Kurtosis	-1.199017016
Mean	757.9444444
Median Absolute Deviation (MAD)	378.5
Skewness	0.001102879266
Sum	1146012
Variance	191668.2113
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	1	0.1%
1007	1	0.1%
1016	1	0.1%
1015	1	0.1%
1014	1	0.1%
1013	1	0.1%
1012	1	0.1%
1011	1	0.1%
1010	1	0.1%
1009	1	0.1%
Other values (1502)	1502	99.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.1%
1	1	0.1%
2	1	0.1%
3	1	0.1%
4	1	0.1%
5	1	0.1%
6	1	0.1%
7	1	0.1%
8	1	0.1%
9	1	0.1%

Value	Count	Frequency (%)
1516	1	0.1%
1515	1	0.1%
1514	1	0.1%
1513	1	0.1%
1512	1	0.1%
1511	1	0.1%
1510	1	0.1%
1509	1	0.1%
1508	1	0.1%
1507	1	0.1%

df_index
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct	1512
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	757.9444444

Minimum	0
Maximum	1516
Zeros	1
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	11.9 KiB

Quantile statistics

Minimum	0
5-th percentile	76.55
Q1	379.75
median	757.5
Q3	1136.25
95-th percentile	1440.45
Maximum	1516
Range	1516
Interquartile range (IQR)	756.5

Descriptive statistics

Standard deviation	437.799282
Coefficient of variation (CV)	0.5776139468
Kurtosis	-1.199017016
Mean	757.9444444
Median Absolute Deviation (MAD)	378.5
Skewness	0.001102879266
Sum	1146012
Variance	191668.2113
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	1	0.1%
1007	1	0.1%
1016	1	0.1%
1015	1	0.1%
1014	1	0.1%
1013	1	0.1%
1012	1	0.1%
1011	1	0.1%
1010	1	0.1%
1009	1	0.1%
Other values (1502)	1502	99.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.1%
1	1	0.1%
2	1	0.1%
3	1	0.1%
4	1	0.1%
5	1	0.1%
6	1	0.1%
7	1	0.1%
8	1	0.1%
9	1	0.1%

Value	Count	Frequency (%)
1516	1	0.1%
1515	1	0.1%
1514	1	0.1%
1513	1	0.1%
1512	1	0.1%
1511	1	0.1%
1510	1	0.1%
1509	1	0.1%
1508	1	0.1%
1507	1	0.1%

titles
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct	1512
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	11.9 KiB

Harith Iskander: I Told You So	1
American Vandal	1
Laerte-se	1
The Eddy	1
Dolly Parton's Heartstrings	1
Other values (1507)	1507

Length

Max length	83
Median length	17
Mean length	19.81812169
Min length	2

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1512 ?
Unique (%)	100.0%

Sample

1st row	Zumbo's Just Desserts
2nd row	Zona Rosa
3rd row	Young Wallander
4th row	You vs. Wild
5th row	You

Common Values

Value	Count	Frequency (%)
Harith Iskander: I Told You So	1	0.1%
American Vandal	1	0.1%
Laerte-se	1	0.1%
The Eddy	1	0.1%
Dolly Parton's Heartstrings	1	0.1%
Franco Escamilla: Por la anécdota	1	0.1%
The OA	1	0.1%
The Open House	1	0.1%
Rattlesnake	1	0.1%
Terrorism Close Calls	1	0.1%
Other values (1502)	1502	99.3%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
the	390	7.7%
of	122	2.4%
a	55	1.1%
in	45	0.9%
to	38	0.7%
	37	0.7%
with	29	0.6%
and	28	0.5%
love	25	0.5%
for	23	0.5%
Other values (2553)	4303	84.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

years
Real number (ℝ_≥0)

Distinct	16
Distinct (%)	1.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2018.143519

Minimum	2001
Maximum	2020
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	11.9 KiB

Quantile statistics

Minimum	2001
5-th percentile	2015
Q1	2017
median	2018
Q3	2020
95-th percentile	2020
Maximum	2020
Range	19
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	1.860071318
Coefficient of variation (CV)	0.0009216744504
Kurtosis	11.48221929
Mean	2018.143519
Median Absolute Deviation (MAD)	1
Skewness	-2.215388351
Sum	3051433
Variance	3.459865309
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=16)

Value	Count	Frequency (%)
2020	386	25.5%
2019	369	24.4%
2018	315	20.8%
2017	212	14.0%
2016	122	8.1%
2015	55	3.6%
2014	22	1.5%
2013	15	1.0%
2012	6	0.4%
2011	4	0.3%
Other values (6)	6	0.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2001	1	0.1%
2003	1	0.1%
2004	1	0.1%
2007	1	0.1%
2008	1	0.1%
2009	1	0.1%
2011	4	0.3%
2012	6	0.4%
2013	15	1.0%
2014	22	1.5%

Value	Count	Frequency (%)
2020	386	25.5%
2019	369	24.4%
2018	315	20.8%
2017	212	14.0%
2016	122	8.1%
2015	55	3.6%
2014	22	1.5%
2013	15	1.0%
2012	6	0.4%
2011	4	0.3%

genres
Categorical

HIGH CARDINALITY

Distinct	247
Distinct (%)	16.3%
Missing	1
Missing (%)	0.1%
Memory size	11.9 KiB

Comedy	316
Documentary	126
Drama	58
Reality-TV	50
Comedy, Drama	41
Other values (242)	920

Length

Max length	34
Median length	15
Mean length	15.38385175
Min length	5

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	111 ?
Unique (%)	7.3%

Sample

1st row	Reality-TV
2nd row	Comedy
3rd row	Crime, Drama, Mystery
4th row	Adventure, Reality-TV
5th row	Crime, Drama, Romance

Common Values

Value	Count	Frequency (%)
Comedy	316	20.9%
Documentary	126	8.3%
Drama	58	3.8%
Reality-TV	50	3.3%
Comedy, Drama	41	2.7%
Documentary, Crime	40	2.6%
Documentary, Comedy	31	2.1%
Animation, Action, Adventure	27	1.8%
Comedy, Drama, Romance	24	1.6%
Comedy, Romance	24	1.6%
Other values (237)	774	51.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
comedy	617	21.0%
drama	449	15.3%
documentary	341	11.6%
crime	187	6.4%
animation	171	5.8%
action	164	5.6%
adventure	125	4.3%
thriller	93	3.2%
short	85	2.9%
romance	83	2.8%
Other values (16)	622	21.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

imdb
Real number (ℝ_≥0)

Distinct	66
Distinct (%)	4.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6.686396815

Minimum	2.4
Maximum	9.3
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	11.9 KiB

Quantile statistics

Minimum	2.4
5-th percentile	4.7
Q1	6
median	6.8
Q3	7.4
95-th percentile	8.3
Maximum	9.3
Range	6.9
Interquartile range (IQR)	1.4

Descriptive statistics

Standard deviation	1.097880497
Coefficient of variation (CV)	0.1641961324
Kurtosis	0.3599492249
Mean	6.686396815
Median Absolute Deviation (MAD)	0.7
Skewness	-0.5586127291
Sum	10109.83198
Variance	1.205341585
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
7.2	69	4.6%
6.8	68	4.5%
7.4	62	4.1%
7.3	60	4.0%
6.4	60	4.0%
6.5	59	3.9%
7.1	56	3.7%
6.3	51	3.4%
6.7	49	3.2%
6.6	47	3.1%
Other values (56)	931	61.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2.4	1	0.1%
2.5	2	0.1%
2.6	1	0.1%
2.9	1	0.1%
3	1	0.1%
3.2	2	0.1%
3.4	3	0.2%
3.5	2	0.1%
3.6	3	0.2%
3.7	1	0.1%

Value	Count	Frequency (%)
9.3	1	0.1%
9.2	1	0.1%
9.1	1	0.1%
8.9	1	0.1%
8.8	6	0.4%
8.7	14	0.9%
8.6	11	0.7%
8.5	10	0.7%
8.4	24	1.6%
8.3	27	1.8%

runtime
Real number (ℝ_≥0)

MISSING

Distinct	182
Distinct (%)	14.3%
Missing	240
Missing (%)	15.9%
Infinite	0
Infinite (%)	0.0%
Mean	74.55424528

Minimum	4
Maximum	629
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	13.4 KiB

Quantile statistics

Minimum	4
5-th percentile	23
Q1	41
median	62
Q3	95
95-th percentile	135.45
Maximum	629
Range	625
Interquartile range (IQR)	54

Descriptive statistics

Standard deviation	59.54394114
Coefficient of variation (CV)	0.7986660037
Kurtosis	26.00040214
Mean	74.55424528
Median Absolute Deviation (MAD)	28
Skewness	4.1616253
Sum	94833
Variance	3545.480926
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
30	84	5.6%
60	82	5.4%
45	41	2.7%
50	33	2.2%
40	31	2.1%
23	30	2.0%
24	29	1.9%
25	27	1.8%
92	20	1.3%
90	19	1.3%
Other values (172)	876	57.9%
(Missing)	240	15.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
4	1	0.1%
7	2	0.1%
10	1	0.1%
11	2	0.1%
12	3	0.2%
13	1	0.1%
14	1	0.1%
15	8	0.5%
16	3	0.2%
17	2	0.1%

Value	Count	Frequency (%)
629	1	0.1%
573	1	0.1%
572	1	0.1%
542	1	0.1%
494	1	0.1%
491	1	0.1%
452	1	0.1%
436	1	0.1%
403	2	0.1%
393	1	0.1%

description
Categorical

HIGH CARDINALITY

Distinct	1471
Distinct (%)	97.3%
Missing	0
Missing (%)	0.0%
Memory size	11.9 KiB

Add a Plot	42
After his sudden firing, a popular radio DJ moves in with his aunt, bringing along his four spoiled children, and a plan to return to the airwaves.	1
Comedian Marc Maron riffs on topics including Donald Trump, a Rolling Stones concert, and the hat-buying experience.	1
In this unrestricted jaunt, comic Jim Norton offers a personal perspective on romance, desire, and sexual proclivities.	1
Mildred lives an ordinary until the day that Maud Spellbody crashes her broomstick into their balcony. Maud then introduces Mildred to Cackle's Academy - a school for young witches set high on a mountaintop.	1
Other values (1466)	1466

Length

Max length	421
Median length	146
Mean length	145.0489418
Min length	10

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1470 ?
Unique (%)	97.2%

Sample

1st row	Amateur Australian chefs compete to impress patisserie chef Adriano Zumbo with their sweet creations. Those who don't fit the brief go head to head in the 'Zumbo test' to replicate his unique desserts.
2nd row	Add a Plot
3rd row	Follow recently graduated police officer Kurt Wallander as he investigates his first case.
4th row	In this interactive series, you'll make key decisions to help Bear Grylls survive, thrive and complete missions in the harshest environments on Earth.
5th row	A dangerously charming, intensely obsessive young man goes to extreme measures to insert himself into the lives of those he is transfixed by.

Common Values

Value	Count	Frequency (%)
Add a Plot	42	2.8%
After his sudden firing, a popular radio DJ moves in with his aunt, bringing along his four spoiled children, and a plan to return to the airwaves.	1	0.1%
Comedian Marc Maron riffs on topics including Donald Trump, a Rolling Stones concert, and the hat-buying experience.	1	0.1%
In this unrestricted jaunt, comic Jim Norton offers a personal perspective on romance, desire, and sexual proclivities.	1	0.1%
Mildred lives an ordinary until the day that Maud Spellbody crashes her broomstick into their balcony. Maud then introduces Mildred to Cackle's Academy - a school for young witches set high on a mountaintop.	1	0.1%
The Rescue Riders have been asked to find a precious golden dragon egg, and keep it safe from evil pirates.	1	0.1%
Comedian Jerry Seinfeld performs at the Beacon Theatre in New York City with his take on everyday life, uncovering comedy in the commonplace.	1	0.1%
Comedian Russell Howard brings his manic energy to a new stand-up special that tackles politics, childhood and why he's a jerk.	1	0.1%
Women's rights attorney Gloria Allred takes on the biggest names in American culture as coverage of sexual assault allegations in the media become more prevalent.	1	0.1%
Hugo Sanchez is tasked with leading the Cuervos into the Duel of the Birds tournament despite his personal life pulling him back toward the family business.	1	0.1%
Other values (1461)	1461	96.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
the	1784	4.9%
a	1595	4.4%
and	1189	3.3%
of	1097	3.0%
to	950	2.6%
in	816	2.2%
his	481	1.3%
with	365	1.0%
on	345	0.9%
her	299	0.8%
Other values (8046)	27623	75.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

stars
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct	1461
Distinct (%)	98.5%
Missing	28
Missing (%)	1.9%
Memory size	11.9 KiB

Nat Faxon, Jay Gragnani, Ramone Hamilton, Sean Astin	3
John Schultz, Rose McIver, Ben Lamb, Alice Krige, Honor Kneafsey	2
Raúl Campos, Jan Suter, Sofia Niño de Rivera	2
Raúl Campos, Jan Suter, Carlos Ballarta	2
Seth Barrish, Mike Birbiglia	2
Other values (1456)	1473

Length

Max length	128
Median length	61
Mean length	58.68328841
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1439 ?
Unique (%)	97.0%

Sample

1st row	Gigi Falanga, Rachel Khoo, Adriano Zumbo
2nd row	Ray Contreras, Pablo Morán, Manu Nna, Ana Julia Yeye
3rd row	Adam Pålsson, Leanne Best, Richard Dillane, Ellise Chappell
4th row	Bear Grylls
5th row	Penn Badgley, Victoria Pedretti, Ambyr Childers, Elizabeth Lail

Common Values

Value	Count	Frequency (%)
Nat Faxon, Jay Gragnani, Ramone Hamilton, Sean Astin	3	0.2%
John Schultz, Rose McIver, Ben Lamb, Alice Krige, Honor Kneafsey	2	0.1%
Raúl Campos, Jan Suter, Sofia Niño de Rivera	2	0.1%
Raúl Campos, Jan Suter, Carlos Ballarta	2	0.1%
Seth Barrish, Mike Birbiglia	2	0.1%
Ulises Valencia, Franco Escamilla	2	0.1%
Bill D'Elia, Chris D'Elia	2	0.1%
Gigi Saul Guerrero	2	0.1%
Marcus Raboy, Vir Das	2	0.1%
Shannon Hartman, Jo Koy	2	0.1%
Other values (1451)	1463	96.8%
(Missing)	28	1.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
michael	79	0.6%
david	77	0.6%
john	72	0.6%
paul	50	0.4%
james	38	0.3%
jay	36	0.3%
mike	36	0.3%
alex	33	0.3%
tom	33	0.3%
chris	32	0.3%
Other values (6380)	11788	96.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

number_of_votes
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	1333
Distinct (%)	88.2%
Missing	1
Missing (%)	0.1%
Infinite	0
Infinite (%)	0.0%
Mean	13386.62078

Minimum	5
Maximum	785704
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	13.4 KiB

Quantile statistics

Minimum	5
5-th percentile	64
Q1	561.5
median	2024
Q3	7642.5
95-th percentile	62663.5
Maximum	785704
Range	785699
Interquartile range (IQR)	7081

Descriptive statistics

Standard deviation	41975.79153
Coefficient of variation (CV)	3.135652545
Kurtosis	104.8427738
Mean	13386.62078
Median Absolute Deviation (MAD)	1792
Skewness	8.383597886
Sum	20227184
Variance	1761967074
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
95	6	0.4%
64	5	0.3%
68	4	0.3%
22	4	0.3%
20	4	0.3%
43	4	0.3%
91	4	0.3%
368	4	0.3%
292	3	0.2%
1852	3	0.2%
Other values (1323)	1470	97.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
5	1	0.1%
7	1	0.1%
8	1	0.1%
9	1	0.1%
10	2	0.1%
11	1	0.1%
12	1	0.1%
16	1	0.1%
17	2	0.1%
18	1	0.1%

Value	Count	Frequency (%)
785704	1	0.1%
459712	1	0.1%
426556	1	0.1%
356368	1	0.1%
345996	1	0.1%
312301	1	0.1%
280280	1	0.1%
279120	1	0.1%
275850	1	0.1%
273062	1	0.1%

type
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	11.9 KiB

TV Show	1008
Movie	504

Length

Max length	7
Median length	7
Mean length	6.333333333
Min length	5

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	TV Show
2nd row	TV Show
3rd row	TV Show
4th row	TV Show
5th row	TV Show

Common Values

Value	Count	Frequency (%)
TV Show	1008	66.7%
Movie	504	33.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
tv	1008	40.0%
show	1008	40.0%
movie	504	20.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

original_plataform
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	11.9 KiB

Netflix	1512

Length

Max length	7
Median length	7
Mean length	7
Min length	7

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Netflix
2nd row	Netflix
3rd row	Netflix
4th row	Netflix
5th row	Netflix

Common Values

Value	Count	Frequency (%)
Netflix	1512	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
netflix	1512	100.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

nueva_columna
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	1499
Distinct (%)	99.2%
Missing	1
Missing (%)	0.1%
Infinite	0
Infinite (%)	0.0%
Mean	0.02037698931

Minimum	1.120014662 × 10^-5
Maximum	1.4
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	13.4 KiB

Quantile statistics

Minimum	1.120014662 × 10^-5
5-th percentile	0.0001200386199
Q1	0.000842121502
median	0.003363518758
Q3	0.01163067093
95-th percentile	0.09676732482
Maximum	1.4
Range	1.3999888
Interquartile range (IQR)	0.01078854942

Descriptive statistics

Standard deviation	0.06851416496
Coefficient of variation (CV)	3.362330123
Kurtosis	145.4942344
Mean	0.02037698931
Median Absolute Deviation (MAD)	0.003030426796
Skewness	9.888435633
Sum	30.78963084
Variance	0.004694190801
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.07065217391	2	0.1%
0.02054380665	2	0.1%
0.001818181818	2	0.1%
0.04705882353	2	0.1%
0.01176470588	2	0.1%
0.001422256391	2	0.1%
0.09375	2	0.1%
0.03414634146	2	0.1%
0.003157894737	2	0.1%
0.004933981932	2	0.1%
Other values (1489)	1491	98.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1.120014662 × 10^-5	1	0.1%
1.892489211 × 10^-5	1	0.1%
2.0630351 × 10^-5	1	0.1%
2.413235756 × 10^-5	1	0.1%
2.422978648 × 10^-5	1	0.1%
2.529610856 × 10^-5	1	0.1%
2.543382004 × 10^-5	1	0.1%
2.925645783 × 10^-5	1	0.1%
2.936378467 × 10^-5	1	0.1%
3.009458298 × 10^-5	1	0.1%

Value	Count	Frequency (%)
1.4	1	0.1%
0.87	1	0.1%
0.7625	1	0.1%
0.56	1	0.1%
0.5555555556	1	0.1%
0.5545454545	1	0.1%
0.5142857143	1	0.1%
0.4833333333	1	0.1%
0.40625	1	0.1%
0.385	1	0.1%

nueva_columna2
Real number (ℝ_≥0)

Distinct	1499
Distinct (%)	99.2%
Missing	1
Missing (%)	0.1%
Infinite	0
Infinite (%)	0.0%
Mean	0.02037698931

Minimum	1.120014662 × 10^-5
Maximum	1.4
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	11.9 KiB

Quantile statistics

Minimum	1.120014662 × 10^-5
5-th percentile	0.0001200386199
Q1	0.000842121502
median	0.003363518758
Q3	0.01163067093
95-th percentile	0.09676732482
Maximum	1.4
Range	1.3999888
Interquartile range (IQR)	0.01078854942

Descriptive statistics

Standard deviation	0.06851416496
Coefficient of variation (CV)	3.362330123
Kurtosis	145.4942344
Mean	0.02037698931
Median Absolute Deviation (MAD)	0.003030426796
Skewness	9.888435633
Sum	30.78963084
Variance	0.004694190801
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.07065217391	2	0.1%
0.001818181818	2	0.1%
0.001422256391	2	0.1%
0.1	2	0.1%
0.003157894737	2	0.1%
0.004933981932	2	0.1%
0.07472527473	2	0.1%
0.03414634146	2	0.1%
0.02054380665	2	0.1%
0.04705882353	2	0.1%
Other values (1489)	1491	98.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1.120014662 × 10^-5	1	0.1%
1.892489211 × 10^-5	1	0.1%
2.0630351 × 10^-5	1	0.1%
2.413235756 × 10^-5	1	0.1%
2.422978648 × 10^-5	1	0.1%
2.529610856 × 10^-5	1	0.1%
2.543382004 × 10^-5	1	0.1%
2.925645783 × 10^-5	1	0.1%
2.936378467 × 10^-5	1	0.1%
3.009458298 × 10^-5	1	0.1%

Value	Count	Frequency (%)
1.4	1	0.1%
0.87	1	0.1%
0.7625	1	0.1%
0.56	1	0.1%
0.5555555556	1	0.1%
0.5545454545	1	0.1%
0.5142857143	1	0.1%
0.4833333333	1	0.1%
0.40625	1	0.1%
0.385	1	0.1%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	level_0	df_index	titles	years	genres	imdb	runtime	description	stars	number_of_votes	type	original_plataform	nueva_columna	nueva_columna2
0	0	0	Zumbo's Just Desserts	2016	Reality-TV	6.9	52	Amateur Australian chefs compete to impress patisserie chef Adriano Zumbo with their sweet creations. Those who don't fit the brief go head to head in the 'Zumbo test' to replicate his unique desserts.	Gigi Falanga, Rachel Khoo, Adriano Zumbo	1779	TV Show	Netflix	0.003879	0.003879
1	1	1	Zona Rosa	2019	Comedy	6.0	<NA>	Add a Plot	Ray Contreras, Pablo Morán, Manu Nna, Ana Julia Yeye	33	TV Show	Netflix	0.181818	0.181818
2	2	2	Young Wallander	2020	Crime, Drama, Mystery	6.7	<NA>	Follow recently graduated police officer Kurt Wallander as he investigates his first case.	Adam Pålsson, Leanne Best, Richard Dillane, Ellise Chappell	5419	TV Show	Netflix	0.001236	0.001236
3	3	3	You vs. Wild	2019	Adventure, Reality-TV	6.7	20	In this interactive series, you'll make key decisions to help Bear Grylls survive, thrive and complete missions in the harshest environments on Earth.	Bear Grylls	1977	TV Show	Netflix	0.003389	0.003389
4	4	4	You	2018	Crime, Drama, Romance	7.8	45	A dangerously charming, intensely obsessive young man goes to extreme measures to insert himself into the lives of those he is transfixed by.	Penn Badgley, Victoria Pedretti, Ambyr Childers, Elizabeth Lail	134932	TV Show	Netflix	0.000058	0.000058
5	5	5	YooHoo to the Rescue	2019	Family	6.9	<NA>	In a series of magical missions, quick-witted YooHoo and his can-do crew travel the globe to help animals in need.	Ryan Bartley, Kira Buckland, Lucien Dodge, Kyle Hebert	37	TV Show	Netflix	0.186486	0.186486
6	6	6	Yankee	2019	Drama	6.0	40	On the run from the police, an Arizona man crosses into Mexico and gets deeply involved in drug trafficking, with the help of modern technology.	Pablo Lyle, Ana Layevska, Pamela Almanza, Sebastián Ferrat	458	TV Show	Netflix	0.0131	0.0131
7	7	7	Wu Assassins	2019	Action, Crime, Drama	6.4	44	A warrior chosen as the latest and last Wu Assassin must search for the powers of an ancient triad and restore balance in San Francisco's Chinatown.	Iko Uwais, Byron Mann, Li Jun Li, Lawrence Kao	9336	TV Show	Netflix	0.000686	0.000686
8	8	8	World's Most Wanted	2020	Documentary, Crime	7.1	<NA>	Heinous criminals have avoided capture despite massive rewards and global investigations. This docuseries profiles five of the world's most wanted.	Jennifer Julian, Thomas Fuentes, Calogero Germaná, David Lorino	1495	TV Show	Netflix	0.004749	0.004749
9	9	9	World of Winx	2016	Animation, Action, Comedy	6.8	30	The Winx travel all over the world searching for talent for WOW. and preventing the mysterious talent thief from kidnapping them.	Rebecca Soler, Alysha Deslorieux, Haven Paschall, Eileen Stevens	556	TV Show	Netflix	0.01223	0.01223

Last rows

	level_0	df_index	titles	years	genres	imdb	runtime	description	stars	number_of_votes	type	original_plataform	nueva_columna	nueva_columna2
1502	1507	1507	Home: For the Holidays	2017	Animation, Short, Adventure	4.8	45	Oh takes it upon himself to introduce Christmas joy to his fellow Boovs. Unfortunately, his well-meaning mission nearly destroys the city.	Blake Lemons, Kelly Clarkson, Ryan Crego, Rachel Crow, Kelly Donohue	104	TV Show	Netflix	0.046154	0.046154
1503	1508	1508	Frankenstein's Monster's Monster, Frankenstein	2019	Short, Comedy	5.9	32	David Harbour delves into the enigmatic history of his legendary acting family, as he examines his father's legacy and role in a made-for-TV play.	Daniel Gray Longino, David Harbour, Kate Berlant, Alex Ozerov, Mary Woronov	1870	TV Show	Netflix	0.003155	0.003155
1504	1509	1509	Captain Underpants: Epic Choice-o-rama	2020	Animation, Short, Action	6.0	<NA>	Add a Plot	Todd Grimes, Nat Faxon, Jay Gragnani, Ramone Hamilton, Sean Astin	64	TV Show	Netflix	0.09375	0.09375
1505	1510	1510	A StoryBots Christmas	2017	Short, Family, Fantasy	6.1	24	When Bo mistakenly thinks that her friends don't like her gifts, she heads to the North Pole to ask Santa for help making better presents. She learns along the way that Christmas is about far more than just the toys.	Jeff Gill, Evan Spiridellis, Judy Greer, Erin Fitzgerald, Fred Tatasciore, Jeff Gill	121	TV Show	Netflix	0.050413	0.050413
1506	1511	1511	A Family Reunion Christmas	2019	Short, Comedy, Family	5.6	28	The McKellans are back to spread Christmas joy in this holiday special about the importance of family, forgiveness, and empathy.	Robbie Countryman, Tia Mowry-Hardrict, Anthony Alabi, Talia Jackson, Isaiah Russell-Bailey	119	TV Show	Netflix	0.047059	0.047059
1507	1512	1512	Ralphie May: Unruly	2015	Comedy	4.7	83	Filmed in front of a raucous crowd, comedian Ralphie May unleashes his hilariously raunchy perspective in his first Netflix original stand-up special.	John Asher, Ralphie May	357	Movie	Netflix	0.013165	0.013165
1508	1513	1513	John Hodgman: Ragnarok	2013	Comedy, Music	6.2	68	The deranged millionaire John Hodgman plays his last Ragnarok stand-up comedy show on the last day of human history: December 21, 2012.	Lance Bangs, John Hodgman, Scott Adsit, Cynthia J. Hopkins, Joel Ronson	292	Movie	Netflix	0.021233	0.021233
1509	1514	1514	Jimmy Carr: Funny Business	2016	Comedy	7.2	62	A man, with an incredibly stupid laugh, tells jokes to an audience.	Sam Wrench, Jimmy Carr	3445	Movie	Netflix	0.00209	0.00209
1510	1515	1515	Anthony Jeselnik: Thoughts and Prayers	2015	Comedy	7.8	59	Stand up comedian and former Late Night with Jimmy Fallon writer Anthony Jeselnik brings his dark humor and wit to San Francisco.	Adam Dubin, Anthony Jeselnik, Peggy	4300	Movie	Netflix	0.001814	0.001814
1511	1516	1516	13th: A Conversation with Oprah Winfrey & Ava DuVernay	2017	Documentary, Short	7.0	37	Oprah Winfrey sits down with other to discuss social and cultural issues.	Oprah Winfrey, Ava DuVernay	174	Movie	Netflix	0.04023	0.04023

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Spearman's ρ

Pearson's r

Kendall's τ

Cramér's V (φc)

Missing values

Sample

First rows

Last rows